TY  - CONF
AU  - Breuer, Thomas
AU  - Cao, Karl-Kiên
AU  - Wetzel, Manuel
AU  - Frey, Ulrich
AU  - Sasanpour, Shima
AU  - Buschmann, Jan
AU  - Böhme, Aileen
AU  - Vanaret, Charlie
TI  - Enabling energy systems research on HPC
M1  - FZJ-2022-04941
PY  - 2022
AB  - Energy systems research strongly relies on large modeling frameworks. Many of them use linear optimization approaches to calculate blueprints for ideal future energy systems, which become increasingly complex, as do the models. The state of the art is to compute them with shared-memory computers combined with approaches to reduce the model size. We overcome this and implement a fully automated workflow on HPC using a newly developed solver for distributed memory architectures. Moreover, we address the challenge of uncertainty in scenario analysis by performing sophisticated parameter variations for large-scale power system models, which cannot be solved in the conventional way. Preliminary results show that we are able to identify clusters of future energy system designs, which perform well from different perspectives of energy system research and also consider disruptive events. Furthermore, we also observe that our approach provides the most insights when being applied to complex rather than simple models.
T2  - The International Conference for High Performance Computing, Networking, Storage, and Analysis
CY  - 13 Nov 2022 - 18 Nov 2022, Dallas (USA)
Y2  - 13 Nov 2022 - 18 Nov 2022
M2  - Dallas, USA
LB  - PUB:(DE-HGF)24
UR  - https://juser.fz-juelich.de/record/911687
ER  -